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The reconstruction of meteorological observations or deterministic predictions for a certain variable and station may be performed with data from other variables at that station, or from other nearby stations. This is a hindcasting problem, known from some time to be solvable using the Analogues Ensemble (AnEn) method. However, depending on the dimension and granularity of the datasets used for the reconstruction, this method may be computationally very demanding, even if parallelization is used. In this paper, the AnEn method is combined with K-means clustering, allowing for a considerable acceleration of the reconstruction task, while keeping the accuracy of the results.